ELECTRICAL ENERGY PRICING USING TECHNICAL FORECASTING MODEL

Abstract

Technology forecasting (TF) has been acknowledged as an effective tool in setting technology strategies. A large number of techniques have been evolved for technology forecasting. The quality of forecasts would greatly depend on proper selection and application of appropriate techniques. The application demands that the technique used needs to be time, space and technology specific. An analysis of the limitations of application of technological forecasting methodologies is indicative of the fact that very little effort is made to select an appropriate technique for a particular technology. Selection of an appropriate technique in a particular situation will affect the accuracy and reliability of the forecast. In this dissertation, forecasting models have been used for examining the energy pricing and growth saturation levels for the Indian energy sector. Two forecasting models namely the Pearl and Gompertz models have been used for forecasting energy pricing and the electrical demand growth in four sub-sectors of the Indian energy demand sector. These sectors are the Residential, commercial. A industrial and agricultural energy demand sectors. The result shows that data of commercial sector is best fitted by the models, while the mean absolute percentage error for industrial sector was the highest.